Power grid section data retrieval method considering manifold sorting algorithm

Abstract

Aiming at the problems of low multi-dimensional query efficiency and incapability of multi-dimensional integral matching of a retrieval result during data retrieval, the invention discloses a power grid section data retrieval method considering a manifold sorting algorithm. The method comprises the following steps: describing power grid section data into corresponding points in a multi-dimensionalvector space, and creating a weighted graph model; acquiring a retrieval result by considering the overall approximate manifold structure of the data, so the retrieval result has relatively high correlation with source query; and distributing the sorting scores by confidence propagation, so that the accuracy of a retrieval result is improved, and the defects of correlation measurement on high-dimensional data query processing are effectively avoided.

Description

technical field [0001] The invention proposes a power grid section data retrieval method considering a manifold sorting algorithm, improves the accuracy of retrieval results, and effectively avoids the deficiency of correlation measurement for high-dimensional data query processing. Background technique [0002] With the passage of time, various measurement data of many nodes in the regional power grid continue to accumulate. These data are one of the supporting elements for building a stable, reliable and efficient smart grid. It not only reflects the regular characteristics of the industry, but also guides power production. It also reflects the development status of the economy and society, and is an important resource for future power development. How to use the existing data analysis technology to quickly retrieve valuable information from the massive cross-sectional data of the power grid, so that power companies can provide customers with better services is a key issue...

AI Technical Summary

Problems solved by technology

[0005] The main problem to be solved by the present invention is: Aiming at the problem that the efficiency of multi-dimensional query is not high during data retrieval, and the retrieval results cannot be matched in multiple dimensions as a whole, the present invention proposes a grid cross-section data retrieval method based on manifold sorting, using low-dimensional Data retrieval is carried out in the manifold subspace, the power grid section data is described as corresponding points in the multidimensional vector space, a weighted graph model is created, and the retrieval results are obtained by considering the overall approximate manifold structure of the data, so that there is a relationship between it and the source query. Higher correlation; improve the original similarity measure based on Euclidean distance, and avoid the dimension disaster problem in massive data retrieval

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